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Stochastic unit commitment in microgrids: Influence of the load forecasting error and the availability of energy storage

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  • Alvarado-Barrios, Lázaro
  • Rodríguez del Nozal, Álvaro
  • Boza Valerino, Juan
  • García Vera, Ignacio
  • Martínez-Ramos, Jose L.

Abstract

A Stochastic Model for the Unit Commitment (SUC) problem of a hybrid microgrid for a short period of 24 h is presented. The microgrid considered in the problem is composed of a wind turbine (WT), a photovoltaic plant (PV), a diesel generator (DE), a microturbine (MT) and a Battery Energy Storage System (BESS). The problem is addressed in three stages. First, based on the historical data of the demanded power in the microgrid, an ARMA model is used to obtain the demand prediction. Second, the 24-h-ahead SUC problem is solved, based on generators’ constraints, renewable generation and demand forecast and the statistical distribution of the error in the demand estimation. In this problem, a spinning reserve of the dispatchable units is considered, able to cover the uncertainties in the demand estimation. In the third stage, once the SUC problem has been solved, a case study is established in real time, in which the demand estimation error in every moment is known. Therefore, the objective of this stage is to select the spinning reserve of the units in an optimal way to minimize the cost in the microgrid operation.

Suggested Citation

  • Alvarado-Barrios, Lázaro & Rodríguez del Nozal, Álvaro & Boza Valerino, Juan & García Vera, Ignacio & Martínez-Ramos, Jose L., 2020. "Stochastic unit commitment in microgrids: Influence of the load forecasting error and the availability of energy storage," Renewable Energy, Elsevier, vol. 146(C), pages 2060-2069.
    • Handle: RePEc:eee:renene:v:146:y:2020:i:c:p:2060-2069
    DOI: 10.1016/j.renene.2019.08.032
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    References listed on IDEAS

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    1. Soshinskaya, Mariya & Crijns-Graus, Wina H.J. & Guerrero, Josep M. & Vasquez, Juan C., 2014. "Microgrids: Experiences, barriers and success factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 659-672.
    2. Ibrahim Alsaidan & Abdulaziz Alanazi & Wenzhong Gao & Hongyu Wu & Amin Khodaei, 2017. "State-Of-The-Art in Microgrid-Integrated Distributed Energy Storage Sizing," Energies, MDPI, vol. 10(9), pages 1-14, September.
    3. Pappas, S.Sp. & Ekonomou, L. & Karamousantas, D.Ch. & Chatzarakis, G.E. & Katsikas, S.K. & Liatsis, P., 2008. "Electricity demand loads modeling using AutoRegressive Moving Average (ARMA) models," Energy, Elsevier, vol. 33(9), pages 1353-1360.
    4. Mohamed Abd el Motaleb, Ahmad & Kazim Bekdache, Sarah & Barrios, Lázaro Alvarado, 2016. "Optimal sizing for a hybrid power system with wind/energy storage based in stochastic environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1149-1158.
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    3. Sandelic, Monika & Peyghami, Saeed & Sangwongwanich, Ariya & Blaabjerg, Frede, 2022. "Reliability aspects in microgrid design and planning: Status and power electronics-induced challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    4. Qing, Ke & Du, Yuefang & Huang, Qi & Duan, Chao & Hu, Weihao, 2024. "Energy scheduling for microgrids with renewable energy sources considering an adjustable convex hull based uncertainty set," Renewable Energy, Elsevier, vol. 220(C).
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    7. Wei Wu & Shih-Chieh Chou & Karthickeyan Viswanathan, 2023. "Optimal Dispatching of Smart Hybrid Energy Systems for Addressing a Low-Carbon Community," Energies, MDPI, vol. 16(9), pages 1-19, April.
    8. Jiang, Sufan & Wu, Chuanshen & Gao, Shan & Pan, Guangsheng & Liu, Yu & Zhao, Xin & Wang, Sicheng, 2022. "Robust frequency risk-constrained unit commitment model for AC-DC system considering wind uncertainty," Renewable Energy, Elsevier, vol. 195(C), pages 395-406.
    9. Yong-Rae Lee & Hyung-Joon Kim & Mun-Kyeom Kim, 2021. "Optimal Operation Scheduling Considering Cycle Aging of Battery Energy Storage Systems on Stochastic Unit Commitments in Microgrids," Energies, MDPI, vol. 14(2), pages 1-21, January.
    10. Tostado-Véliz, Marcos & León-Japa, Rogelio S. & Jurado, Francisco, 2021. "Optimal electrification of off-grid smart homes considering flexible demand and vehicle-to-home capabilities," Applied Energy, Elsevier, vol. 298(C).
    11. Tostado-Véliz, Marcos & Kamel, Salah & Aymen, Flah & Rezaee Jordehi, Ahmad & Jurado, Francisco, 2022. "A Stochastic-IGDT model for energy management in isolated microgrids considering failures and demand response," Applied Energy, Elsevier, vol. 317(C).
    12. Harsh, Pratik & Das, Debapriya, 2022. "Optimal coordination strategy of demand response and electric vehicle aggregators for the energy management of reconfigured grid-connected microgrid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    13. Jing Liu & Xin-Lei Zhou & Lu-Qi Zhang & Yue-Ping Xu, 2023. "Forecasting Short-term Water Demands with an Ensemble Deep Learning Model for a Water Supply System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(8), pages 2991-3012, June.
    14. Manzano, J.M. & Salvador, J.R. & Romaine, J.B. & Alvarado-Barrios, L., 2022. "Economic predictive control for isolated microgrids based on real world demand/renewable energy data and forecast errors," Renewable Energy, Elsevier, vol. 194(C), pages 647-658.

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